2026 U.S Summer Internship Program: Statistics and Quantitative Sciences Intern
Takeda is a global, R&D-driven biopharmaceutical leader committed to delivering life-transforming treatments. The Statistics and Quantitative Sciences Intern will gain hands-on experience in applying statistical methodologies to drug development and clinical trial analyses while contributing to key program activities.
Responsibilities
- Conduct literature reviews and contribute to the prediction model development using various statistical methodologies
- Perform data analysis using SAS, R or python
- Support internal activities like team meetings in preparation of key program activities
- Use of AI enabled tools for efficiency in documents process
- Communicate findings and results effectively with cross-functional teams through written reports and oral presentations
Skills
- Must be pursuing a PhD in Biostatistics
- Strong understanding of machine learning concepts and their applications
- Experience in applying machine-learning methods to predict treatment outcome based on baseline characteristics and selected post baseline biomarkers
- Familiarity with statistical techniques of model development and parameter tuning
- Proficiency in SAS and R programming languages for data manipulation and statistical analysis
- Python experience is a plus
- Must be authorized to work in the U.S. on a permanent basis without requiring sponsorship
- Must be currently enrolled in a degree program graduating December 2026 or later
- The intern must be able to commit to one of these time frames
- Able to work full time 40 hours a week during internship dates
Benefits
- Paid sick time
- Civic Duty paid time off
- Participation at company volunteer events
- Participation at company sponsored special events
- Access to on-site fitness center (where available)
- Commuter Benefit: To offset your work-commute expenses, Takeda provides U.S. employees with a fixed monthly subsidy to be used for either public transportation (transit) or parking.
Company Overview
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